Human anatomy has traditionally been a descriptive rather than an objective science. Except for measurement protocols for skeletal morphology developed by physical anthropologists, there has been very little data developed to define human morphology. For descriptive purposes classic anatomists have describe the human body as being placed in the “anatomical position”. When in anatomical position the body is standing erect with the arms at the sides with the palms of the hands facing forward. The feet are flat on the ground with the toes pointing forward. Structure location is always described relative to other anatomical features. For example the feet are inferior to the head, the ribs are superficial to the heart, the elbows are lateral to the body and the fingers are distal to the elbow.
Without implementation of a fixed coordinate system linked to specific anatomical landmarks, the possibility to define specific quantitative data to be used to describe the specific location and orientation of any anatomy feature of any individual or population does not exist. The absence of a quantitative information on human anatomy also impacts clinical medicine. Radiologists are trained to recognize patterns of anatomy as displayed in medical images. Until late in the 20th century these images were primarily planar x-ray films. With the advent of CT, MR and PET scanning during the past 3 decades, the types of images that radiologists evaluate have varied along with the methods for how they are obtained, but the images remained primarily planar in format. Identification and extraction of quantitative anatomical data from three dimensional medical images consumes a vast amount of workflow in medicinal diagnostics. The inefficiency is partially due to difficulties in generalizing the steps needed for successful image segmentation of medical imaging data.
The interface between the medical image scanning technology and the patient in today's imaging facilities is the radiology technician, who undergoes one to two years of training on basic human anatomy and imaging technology. Medical imaging technology has advanced to the point that the imaging devices can capture and format the image data in a very short period of time. At the same time medical instrumentation has become so sophisticated that more and more expertise and time is required in the pre-scanning steps to program the device to collect the correct image data.
Only recently has volumetric medical image data been possible to obtain, and few if any processes are in place to effectively clinically evaluate this volumetric data. Most often even though the image data is obtained as digital volumetric data sets, a series of 2D images are provided to the radiologist with which to make his clinical diagnosis. Computer technology currently plays very little role in the analysis of any medical images in regards to assisting the physician in making a differential diagnosis. Furthermore, radiologists today treat each patient as a new unique set of images for which he diagnoses pathology evident in the images based on his experience and expertise in recognizing specific patterns in medical image patterns representing the patient's morphology. This approach is extremely inefficient, expensive and time consuming. This approach also fails to utilize any technology resources to assist the physician with medical image analysis.
Much of the information contained in the volumetric image data is not taken into consideration because physicians currently do not have a recognized approach for utilizing the information and do not have reference normative data on which to base any level of diagnostic decision. The rows and column array format of digital voxel data that is typical of most all volumetric medical images lends itself perfectly for the application of computer technology, but lack of a standard format and orientation for human anatomical image data has hindered the use of computer technology in any type of analysis of medical images. In many instances, the analysis of the structure occurs in isolation, without a comparison to a “normative” dataset of similar anatomical structures. Computer technology will never play a significant role in medical image analysis until a standardized coordinate system and a supporting set of validated statistical data regarding the morphological organization of the human body are available.
Even current computerized, semi-automated techniques employed to analyze medical images require heavy user intervention, resulting in high variability in quantification. U.S. patent application Ser. No. 10/271,916 provides a semi-automated system that attempts to reduce the labor, while increasing the accuracy using seeded region and snake segmentation methods. Even in the more simplified semi-automated techniques, experienced radiologists are needed to provide initial input, generally by outlining a structure of interest. The accuracy of this initial input affects all further processing. Differences in the examining radiologist and the fatigue of the radiologist affect the segmentation input and impact the reliability of the data obtained. Moreover, many of these processes use 2D images to extract information.
The enumerated issues with traditional anatomical diagnosis affects the quality of the medical diagnosis and treatment provided to patients. The field therefore needs a means by which to establish the normative human morphology data necessary to implement at the very least, first pass, computer-based analysis of all volumetric medical image data. Ultimately this will result in faster, more accurate diagnosis of all medical conditions that rely in some part on medical image information in making a differential diagnosis.